python - 如何使用Python循环删除包含特定单词的行？

Question

我想删除所有包含“Scheduled”的行并将其导出到新的 csv 文件。我的代码有什么问题吗？我没有收到任何错误消息，它运行没有问题，但没有任何反应。

这是我的代码:

def scrape(urls):
    browser = webdriver.Firefox()
    for url in urls:
        browser.get(url)
        html = browser.page_source
        soup=BeautifulSoup(html,"html.parser")
        table = soup.find('table', { "class" : "table table-condensed table-hover data-table m-n-t-15" })
        soup2=BeautifulSoup(html,"html.parser")
        name = soup2.h2.string
        datatable=[]
        for record in table.find_all('tr', class_="hidden-xs hidden-sm ng-scope"):
            temp_data = []
            temp_data.append(name)    
            for data in record.find_all("td"):
                temp_data.append(data.text.encode('latin-1'))
            newlist = filter(None, temp_data)
            datatable.append(newlist)
        print name
        output.writerows(datatable)

        def filter_unwanted_words():
            unwanted_words = {'Scheduled'}
            with open('output.csv', 'r') as f:
                for line in f:
                    if set(line.split()).isdisjoint(unwanted_words):
                        yield line


        def write_output():
            with open('output2.csv', 'w') as f:
                f.writelines((line for line in filter_unwanted_words()))

        if __name__ == '__main__':
            write_output()

    resultcsv.close()
    time.sleep(10) 
    browser.close()

我尝试使用这个 def filter_unwanted_words，但它不起作用。

数据表:

Answer 1

替代解决方案。考虑使用 Pandas 将其读取到 Dataframe。

import pandas as pd

data = [[123,1,"Scheduled"],[345,2,"-"]]

df = pd.DataFrame(data)
df[df[2] != "Scheduled"] # filters with 2 being the column that has the value
df.to_csv("output.csv", header=False) # no headers

数据框如下所示:

    0       1   2
0   123     1   Scheduled
1   345     2   -

数据看起来像这样，“预定”被过滤掉:

    0       1   2
1   345     2   -

<小时/>

更通用的解决方案，过滤掉所有“预定”，无论它们位于何处:

import pandas as pd

data = [[123,1,"Scheduled"],[345,2,"-"]]

df = pd.DataFrame(data)
mask = np.column_stack([df[col].astype(str).str.contains(r"Scheduled", na=False) for col in df])
df2 = df.loc[~mask.any(axis=1)]
df2.to_csv("output.csv", header=False) # no headers